Lung Cancer Tissues Research Articles

LncRNA MIR100HG affects the proliferation and metastasis of lung cancer cells through mediating the microRNA-5590-3p/DCBLD2 axis.

The aim of this paper is to investigate the effect of long noncoding RNA (lncRNA) MIR100HG on the proliferation and metastasis of lung cancer cells by mediating the microRNA (miR)-5590-3p/DCBLD2 axis. RNA levels of MIR100HG, miR-5590-3p, and DCBLD2 in lung cancer tissues and cells were detected by quantitative reverse-transcription polymerase chain reaction, and protein level was assessed by Western blot. Effects of MIR100HG or miR-5590-3p on proliferation, migration, and invasion of lung cancer cells were detected by Cell Counting Kit-8, colony formation, and Transwell assays. Luciferase reporter assay and RNA-immunoprecipitation assay confirmed the target relationship between miR-5590-3p and MIR100HG or DCBLD2. MIR100HG and DCBLD2 were highly expressed, while miR-5590-3p was lowly expressed in lung cancer tissues and cells. Silencing MIR100HG or upregulating miR-5590-3p impeded lung cancer cell proliferation, migration, and invasion. MIR100HG could up-regulate DCBLD2 by sponging miR-5590-3p. Downregulation of miR-5590-3p partly overturned the suppressive effect of silencing MIR100HG on lung cancer cell proliferation and metastasis, and overexpression of DCBLD2 also reversed the effect of overexpression of miR-5590-3p on lung cancer cell proliferation and metastasis. LncRNA MIR100HG promotes lung cancer progression by targeting and negatively regulating DCBLD2 through binding with miR-5590-3p.

Linc00958 Promotes Lung Cancer Proliferation and Migration Through Regulating microRNA-490-3p

This study aimed to investigate the role of long intergenic non-protein coding RNA 00958 (Linc00958) in lung cancer (LCa) progression and its underlying mechanism. The study assessed Linc00958 expression in LCa tissues and adjacent tissues using qRT-PCR, and its impact on patient prognosis was analyzed through Kaplan-Meier survival analysis. Additionally, Linc00958 expression in LCa and normal lung cell lines was examined in vitro. Functional assays, including CCK-8, EdU, and transwell assays, were conducted to evaluate the effects of Linc00958 knockdown on LCa cells. To uncover the molecular mechanism, a dual-luciferase reporter assay was used to confirm the binding relationship between Linc00958 and microRNA-490-3p, a downstream gene. Co-transfection experiments were performed to elucidate microRNA-490-3p’s role in Linc00958’s impact on LCa cell functions. The results showed that Linc00958 was overexpressed in LCa tissues and cells, and high Linc00958 expression correlated with reduced patient survival. in vitro experiments revealed that Linc00958 promoted tumor proliferation and migration in LCa cells. Both computational predictions and dual-luciferase reporter assays demonstrated binding sites between microRNA-490-3p and Linc00958. Co-transfection experiments confirmed that Linc00958 facilitated LCa cell proliferation and migration through modulating microRNA-490-3p expression. In summary, Linc00958 promotes LCa cell proliferation and migration by regulating microRNA-490-3p.

EIF4A3 modulated circ_000999 promotes epithelial-mesenchymal transition in cadmium-induced malignant transformation through the miR-205-5p/ZEB1 axis

Cadmium (Cd) is an accumulative toxic metal which poses a serious threat to human health, even in trace amounts. One of the most important steps in the pathophysiology of lung cancer (LC) is the epithelial-mesenchymal transition (EMT). In this investigation, a cell malignant transformation model was established by exposing human bronchial epithelial cells (16HBE) to a low dose of Cd for 30 weeks, after which a highly expressed circular RNA (circ_000999) was identified. Cd-induced EMT was clearly observed in rat lungs and 16HBE cells, which was further enhanced following circ_000999-overexpression. Furthermore, upregulated EIF4A3 interacted with the parental gene AGTPBP1 to promote high expression of circ_000999. Subsequent experiments confirmed that circ_000999 could regulate the EMT process by competitively binding miR-205-5p and inhibiting its activity, consequently upregulating expression of zinc finger E-box binding protein 1 (ZEB1). Importantly, the circ_000999 expression level in LC tissues was significantly increased, exhibiting a strong correlation with EMT indicators. Overall, these findings provide a new objective and research direction for reversing lung EMT and subsequent treatment and prevention of LC.

Autonomous enzymatic synthesis of functional nucleic acids for sensitive measurement of long noncoding RNA in human lung tissues

Aberrant long noncoding RNA (lncRNA) expression is linked to varied pathological processes and malignant tumors, and lncRNA can serve as potential disease biomarkers. Herein, we demonstrate the autonomous enzymatic synthesis of functional nucleic acids for sensitive measurement of lncRNA in human lung tissues on the basis of multiple primer generation-mediated rolling circle amplification (mPG-RCA). This assay involves two padlock probes that act as both a detection probe for recognizing target lncRNA and a domain for producing complementary DNAzyme. Two padlock probes can hybridize with target lncRNA at different sites, followed by ligation to form a circular template with the aid of RNA ligase. The circular template can initiate mPG-RCA to generate abundant Mg2+-dependent DNAzymes that can specifically cleave signal probes to induce the recovery of Cy3 fluorescence. The inherent characteristics of ligase-based ligation reaction and DNAzymes endow this assay with excellent specificity, and the introduction of multiple padlock probes endows this assay with high sensitivity. This strategy can rapidly and sensitively measure lncRNA with a wide linear range of 1 fM − 1 nM and a detection limit of 678 aM within 1.5 h, and it shows distinct advantages of simplicity and immobilization-free without the need of precise temperature control and tedious procedures of nanomaterial preparation. Moreover, it enables accurate measurement of lncRNA level in normal cells and malignant tumor cells as well as differentiation of lncRNA expressions in tissues of non-small cell lung cancer (NSCLC) patients and normal individuals, with promising applications in biomedical studies and disease diagnosis.

Differential Expression of Annexin A1 Protein in Colorectal, Lung, and Liver Cancer Tissues

Differential Expression of Annexin A1 Protein in Colorectal, Lung, and Liver Cancer Tissues

DeepTree: Pathological Image Classification Through Imitating Tree-Like Strategies of Pathologists.

Digitization of pathological slides has promoted the research of computer-aided diagnosis, in which artificial intelligence analysis of pathological images deserves attention. Appropriate deep learning techniques in natural images have been extended to computational pathology. Still, they seldom take into account prior knowledge in pathology, especially the analysis process of lesion morphology by pathologists. Inspired by the diagnosis decision of pathologists, we design a novel deep learning architecture based on tree-like strategies called DeepTree. It imitates pathological diagnosis methods, designed as a binary tree structure, to conditionally learn the correlation between tissue morphology, and optimizes branches to finetune the performance further. To validate and benchmark DeepTree, we build a dataset of frozen lung cancer tissues and design experiments on a public dataset of breast tumor subtypes and our dataset. Results show that the deep learning architecture based on tree-like strategies makes the pathological image classification more accurate, transparent, and convincing. Simultaneously, prior knowledge based on diagnostic strategies yields superior representation ability compared to alternative methods. Our proposed methodology helps improve the trust of pathologists in artificial intelligence analysis and promotes the practical clinical application of pathology-assisted diagnosis.

Oncogenic circ-SLC16A1 promotes progression of non-small cell lung cancer via regulation of the miR-1287-5p/profilin 2 axis

BackgroundCircular RNAs (circRNAs) are single-stranded RNAs with covalently closed structures that have been implicated in cancer progression. However, the regulatory mechanisms remain largely unclear. So, the aim of this study was to reveal the role and regulatory mechanisms of circ-SLC16A1.MethodsIn this study, next-generation sequencing was used to identify abnormally expressed circRNAs between cancerous and para-carcinoma tissues. Fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction were performed to assess the expression patterns of circ-solute carrier family 16 member 1 (SLC16A1) in non-small cell lung cancer (NSCLC) cells and tissue specimens. The dual-luciferase reporter assay was utilized to identify downstream targets of circ-SLC16A1. Transwell migration, wound healing, 5-ethynyl-2′-deoxyuridine incorporation, cell counting, and colony formation assays were conducted to assess the proliferation and migration of NSCLC cells. A mouse tumor xenograft model was employed to determine the roles of circ-SLC16A1 in NSCLC progression and metastasis in vivo.ResultsThe results found that circ-SLC16A1 was upregulated in NSCLC cells and tissues. Downregulation of circ-SLC16A1 inhibited tumor growth by reducing proliferation, lung metastasis, and lymphatic metastasis of NSCLC cells, and arrested the cell cycle in the G1 phase. Also, silencing of circ-SLC16A1 promoted apoptosis of NSCLC cells. The results of bioinformatics analysis and the dual-luciferase reporter assay confirmed that microRNA (miR)-1287-5p and profilin 2 (PFN2) are downstream targets of circ-SLC16A1. PFN2 overexpression or circ-SLC16A1 inhibition restored proliferation and migration of NSCLC cells after silencing of circ-SLC16A1. PFN2 overexpression restored migration and proliferation of NSCLC cells post miR-1287-5p overexpression.ConclusionsCollectively, these findings show that miR-1287-5p/PFN2 signaling was associated with downregulation of circ-SLC16A1 and reduced invasion and proliferation of NSCLC cells. So, circ-SLC16A1 is identified as a mediator of multiple pro-oncogenic signaling pathways in NSCLC and can be targeted to suppress tumor progression.

Abstract 6217: Differential genome-wide gene regulatory networks for lung cancer

Abstract Background: Lung cancer remains the leading cause of cancer death worldwide due to the fact that most cases are diagnosed at distant stages, and treatment is less effective. During the past two decades, much effort has been devoted to understanding tumor biology and developing targeted therapeutics, which have significantly improved patient survival. With the increasingly available multi-omics data from healthy controls and lung cancer patients, we constructed gene regulatory networks for the two main subtypes of non-small-cell lung cancer (NSCLC), the most common type of lung cancer. In addition, differential networks were constructed by integrative analysis of data from lung cancer tissue and tissues from healthy lungs. Methods: Transcriptomics and genomic data were obtained from the patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissue available in The Cancer Genome Atlas (TCGA) project, and both types of omics data of normal lung tissue were downloaded from The Genotype-Tissue Expression (GTEx) consortium. The networks for each subtype and the differential networks were constructed by utilizing our newly developed machine learning tools, two-stage penalized least square (2SPLS) approach, and analysis of variance of directed networks (NetANOVA), respectively. Results: For the top three identified subnetworks of LUAD, we identified some well-known genes associated with lung cancer, such as EGFR, IRF1, KRAS, ERBB2, PIK3CA, MYC, at bootstrap frequency >90%. Based on the top three subnetworks with a bootstrap frequency of 100%, results from the Ingenuity Pathway Analysis (IPA) indicated several significant pathways, primary immunodeficiency signaling and communication between innate and adaptive immune cells. GO enrichment analysis showed statistically significant biological processes, including immune response, extracellular matrix organization, and significant KEGG pathways such as Hematopoietic cell lineage. The differential networks between LUAD, LUSC, and healthy lungs showed the same regulations across all three groups, such as the regulation between EEF2 and RACK1, the perturbations between LUAD and healthy (two-way regulations between HIGD2A and ARL10), and LUSC and healthy (GRB14 regulates EIF3E) respectively. In addition, we identified the differences between LUAD and LUSC, such as bi-directional regulations between CLTB and ARL10. Conclusion: Although all groups share most regulations, we identified differential gene regulations between healthy lung tissue and lung cancer tissue and between LUAD and LUSC of NSCLC. Using multi-omics data generated from lung tissues, coupled with advanced machine learning methods, the causal relationships between genome-wide genes from the analysis will help us understand the molecular mechanism of lung cancer and facilitate the development of personalized treatment strategies. Citation Format: Min Zhang, Zhongli Jiang, Dabao Zhang. Differential genome-wide gene regulatory networks for lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6217.

Abstract 2800: Shotgun metagenomics of COPD-associated lung cancer tissue microbiome

Abstract The gut microbiome plays a crucial role in the development of multiple chronic diseases. Several solid tumors including lung cancer are also implicated in the gut microbiome in cancer initiation and progression, possibly affecting signaling pathways in the tumor microenvironment. However, the microbiome in the peripheral lung tissue is unexplored and their relationship to the lung tumor microenvironment is still unknown. Thus, to explore the relationship between the microbiome and the tumor microenvironment of lung cancer, we performed shotgun metagenomic sequencing of the lung cancer tissue, especially in lung cancer patients accompanied by chronic obstructive pulmonary disease (COPD). We confirmed the presence of a diverse microbiome in peripheral lung cancer tissue. Next, we focused on individual species. We observed significant differences in the relative abundance of several species between COPD and non-COPD patients, and cancer and non-cancer tissue. Then, we focused on the metagenomic diversity between samples. The number of species in COPD patients and cancer tissue were decreased. And the bacterial total abundance in each sample were observed similar trend. On the other hand, alpha diversity in each sample were showed different trend to them. In the analysis of beta diversity using Principal Coordinate Analysis (PCoA), clusters were formed in each group. These findings suggest that microbiome imbalance known as dysbiosis in the peripheral lung tissue may affect the tumor microenvironment resulting in cancer progression. Citation Format: Atsushi Matsuoka, Kazuhiko Shien, Shuta Tomida, Daisuke Mizuno, Masayoshi Ohki, Ryo Yoshichika, Tomohiro Higashihara, Naohiro Hayashi, Fumiaki Mukohara, Mao Yoshikawa, Ken Suzawa, Hiromasa Yamamoto, Shinichi Toyooka. Shotgun metagenomics of COPD-associated lung cancer tissue microbiome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2800.

Abstract 1722: Subtype classification of small cell lung cancer (SCLC) tissues using the EpiCheck methylation sensitive restriction-based PCR platform

Abstract Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with poor survival rates. Despite molecular and clinical heterogeneity, SCLC is currently treated as a single entity without guidance of predictive biomarkers leading to expectedly poor outcomes. A recent study suggested classifying SCLC into four subtypes (“A”, “N”, “P” and “I”), each with unique molecular features and therapeutic vulnerabilities. While initially this classification was based on gene expression (RNA-seq) data, subsequent data suggest it can be recapitulated using reduced-representation bisulfite sequencing (RRBS) methylation profile. While the classification system accurately predicts responses to therapies, including immunotherapies, in retrospective analysis, both tissue-based RNAseq and RRBS are cumbersome, time-consuming and impractical for prospective treatment assignment in an aggressive malignancy. In this pilot study, we developed a methylation-based PCR assay for classification of SCLC subtypes based on the EpiCheck platform, which combines methylation-sensitive restriction endonuclease (MSRE) digestion with qPCR amplification to detect differential methylation at the DNA level. We developed a 13-marker assay and successfully classified, in a blinded study, 96.55% of FFPE tissue samples originating from SCLC patient of A, N and P subtypes. First, a bioinformatic analysis identified 41 candidate biomarkers that are differentially methylated between pairs of SCLC subtypes (A-N, A-P, and N-P) using RRBS data from 56 RNA-seq classified SCLC tumor samples (34 “A”, 19 “N”, 3 “P”). Development of primers and probes for these markers was followed by a biochemical selection process, identifying 13 markers that displayed optimal performance. A PCR EpiCheck assay, employing these 13 markers, was applied to a blinded set of 29 DNA samples from SCLC FFPE tumor tissues (21 “A”, 6 “N”, 2 “P”). Each sample received two ranks based on methylation levels of 5 A-N and 9 P-AN markers and was classified using determined thresholds for each rank. Finally, when comparing PCR-based and RNA-seq-based classifications, the 13-marker PCR assay classified 28/29 (96.55%) of the samples concordantly, misclassifying one "P" sample as "A". This pilot demonstrates the potential of a simple PCR EpiCheck-based assay to accurately differentiate between SCLC subtypes. For complete subtype classification, “I” markers need to be added to the panel, and the assay should be further validated using a larger cohort, particularly for the “P” subtype. Early detection and classification are critical for timely personalized therapy, and such an assay, performed on cfDNA samples, could potentially be used to shorten the time between a patient diagnosis and tailored treatment initiation or clinical study inclusion from a month in best case scenarios to a few days. Citation Format: Orna Savin, Dvir Netanely, Simon Heeke, Carl Michael Gay, Marcos Roberto Estecio, Shacade Danan, Sarah Zaouch, Aharona Shuali, Mathias Ehrich, Lauren Averett Byers, John Victor Heymach, Adam Wasserstrom, Danny Frumkin. Subtype classification of small cell lung cancer (SCLC) tissues using the EpiCheck methylation sensitive restriction-based PCR platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1722.

Abstract 5508: Single-cell spatial landscape of the mutation-specific human lung tumor immune microenvironment

Abstract Background: Therapies targeting immune checkpoint have significantly transformed the treatment of several cancers, including lung cancer. However, only 20% of lung cancer patients show a response to immunotherapies. KRAS and EGFR mutations are significant factors in the development and progression of lung cancer and its response to immunotherapy. Hence, it's vital to understand intra-tumoral heterogeneity, the makeup of the Tumor Microenvironment (TME), and the cellular interactions in tumors with KRAS and EGFR mutations to uncover new insights. Methods: Lung cancer tissues from 200 patients were collected, focusing on KRAS and EGFR mutation statuses, specifically KRAS+/EGFR-, KRAS-/EGFR+, and KRAS-/EGFR-. For each patient, two samples were taken, resulting in a total of 400 tissue microarray (TMA) cores. These samples were imaged at single-cell resolution using the PhenoCycler®-Fusion system, which employed a 42-plex antibody panel targeting immune, tumor, proliferation, and apoptosis markers. The first step in the analysis was cell segmentation, performed using a fine-tuned deep learning model. This process successfully segmented a total of 2.16 million cells across the entire collection of samples. Following this, the protein expressions for each cell were calculated, and unsupervised clustering was performed, resulting in 36 distinct clusters, that were manually annotated into 14 cell phenotypes. The proportions of these cell phenotypes were then quantified for each of the 400 TMA cores and compared across the three mutation groups. The analysis also included the spatial proximity and cellular neighborhoods in relation to these mutation groups. Results: Quantitative analysis focusing on the relative abundance of cell types revealed that the ratio of tumor cells to immune cells was significantly lower in KRAS-/EGFR- tumors compared to those with KRAS+/EGFR- and KRAS-/EGFR+ mutations. Furthermore, the percentages of Regulatory T cells (Tregs) and M1 Macrophages were significantly higher in the KRAS+/EGFR- group compared to the KRAS-/EGFR+ group. Spatial proximity analysis indicated that in the KRAS-/EGFR+ group, M2 Macrophages were significantly closer to Cytotoxic T cells and Helper T cells compared to the distances observed in the other two groups. Moreover, neighborhood analysis identified 20 distinct cellular neighborhoods, each defined by specific cell-cell interactions. COX hazard analysis based on these cellular neighborhoods demonstrated notable variations among the three mutation groups, which are linked to differences in patient outcomes. Conclusions: Through single-cell spatial phenotyping, this work has shown that the spatial immune landscape of lung tumors is influenced by KRAS and EGFR mutation statuses. This presents a novel opportunity to enhance our understanding of the spatial structure of lung cancer and to identify more effective therapeutic targets. Citation Format: Rajender Nandigama, Bassem Ben Cheikh, Ning Ma, Jochen Wilhelm, Laura Klotz, Florian Eichhorn, Mark Kriegsmann, Marek Bartkuhn, Jamal Nabhanizadeh, Sascha Seidel, Thorsten Stiewe, Albrecht Stenzinger, Andreas Weigert, Mario Looso, Friedrich Grimminger, Werner Seeger, Soni Savai Pullamsetti, Niyati Jhaveri, Hauke Winter, Rajkumar Savai. Single-cell spatial landscape of the mutation-specific human lung tumor immune microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5508.

Abstract 4379: RING1, a novel E3 ubiquitin ligase for CIP2A, negatively regulates smoking-induced lung tumorigenesis

Abstract Lung cancer is the second incidence rate of all new cancer diagnoses and the leading cause of cancer-related deaths globally. To develop novel diagnostic and therapeutic targets for lung cancer, there are emerging needs for molecular biological research on the occurrence and progression. Among the targets, CIP2A has been studied for promoting various cancer types, but detailed underlying mechanisms are needed to be further investigated. In this study, it was verified that CIP2A is overexpressed in lung cancer tissues, particularly amongst those with a smoking history, compared to adjacent normal tissues. CIP2A knockdown in lung cancer cells efficiently reduced cell proliferation and migration capacity. Through the mass spectrometry analysis on A549 cells overexpressing CIP2A, RING1 was identified as a candidate for E3 ligase of CIP2A. The interaction of the two proteins and ubiquitin chain regulation by RING1 was verified by immunoprecipitation. RING1 knockdown enhanced proliferation and migration of lung cancer cells, and these effects result from the upregulation of CIP2A and its downstream molecules, c-Myc and cyclin B1. To further study a trigger for RING1 expression changes in lung tumorigenesis, cigarette smoke extract (CSE) was applied for the following experiments. CSE treatment depleted RING1 mRNA, including protein expression. Decreased RING1 level led to upregulation of CIP2A and c-MYC. Collectively, these results reveal novel roles of the RING1 and CIP2A in lung cancer progression caused by smoking and propose a potential biomarker candidate for the therapeutic and diagnostic targets. Citation Format: In-ho Jeong, Chang-Whan Peter Lee, Hwan Jung Lim, Seong Jun Park, Ji Young Hyun. RING1, a novel E3 ubiquitin ligase for CIP2A, negatively regulates smoking-induced lung tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4379.

Abstract 4242: Preserving lung cancer patient mutations in 3D organoid models: Advancing cancer research through innovative culture systems

Abstract Lung cancer is one of the most prevalent cancers worldwide. There are currently many anticancer drugs available, but they have numerous issues in terms of treatment, such as drug resistance and recurrence. Culturing systems that can replace a patient's cancer tissue are crucial, and the existing 2D culturing systems have many limitations. Patient-derived cancer organoid culture is the most advanced culture system for understanding mechanism of cancers. Using a 3D organoid culture system, we have successfully established a culture system for lung cancer using biopsy/surgical specimens and malignant effusions, including a long-term culture system. There are two critical indicators to determine the success of 3D organoid culture. One is whether the organoids retain their cancer-specific mutations from patient’s lung cancer tissue, and the second is whether the organoids grow well and can be maintained in long-term culture for more than 20-30 passages. We typically assess gene mutations in EGFR, ALK, ROS, and P53 when evaluating lung cancer organoids. We confirm these mutations when we establish organoids. and currently we have established a total of 127 patient-derived lung cancer organoids. Among the 127 organoids, we completed NGS analysis on 108 of them and validated that 86.5% exhibit similarity when compared to lung cancer tissues. Additionally, we achieved a 100% retention of mutations in the long-term culturing of these organoids. Our studies indicate that patient-derived lung cancer organoids represent a meaningful organoid system for cancer tissue replacement and treatment response in the context of precision cancer medicine. Citation Format: Ji-yeon Park, Seo Rin Gu, Jiyeon Lee, Na-Gyeong Lee, Dojin Choi, Sang Eun Park, Ji Min Kim, Jinguen Rheey. Preserving lung cancer patient mutations in 3D organoid models: Advancing cancer research through innovative culture systems [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4242.

Abstract 4250: Adherent and spheroid cell models of patient-derived xenograft for drug development and translational research

Abstract Introduction: The development of new drugs in cancer therapy comprises toxicity and efficacy tests with increasing complexity. First and foremost, in vitro experiments are performed with well-established cancer cell lines, which are subsequently validated in animal experiments as prerequisite for clinical trials. Until a few years ago, there were gaps in the complexity chain between in vitro and in vivo experiments. Ethical considerations have led to use of systems like organ on a chip or mini-organ 3D in vitro models. In cancer research, cell cultures or organoids are generated from patient tumor material. However, these cultures only reflect the tumor of one patient, which is why panels of patient tumors should be used to evaluate the effectiveness of drugs on different patients. In vivo panel screens of patient derived xenografts (PDX) mouse models need high numbers of animals and takes several months. A pre-screen with in vitro models generated from in vivo PDX tissues allows large scale and faster pre-screens complementing in vivo systems for more focused in vivo analyses. Methods: Currently we have a pool of more than 600 established PDX models of 21 tumor entities. From this pool, cancer tissues of glioblastoma, mesothelioma, gastric, head/neck, lung and breast cancer were processed in single cell suspensions and cultured under defined conditions to obtain adherent cells or spheroids. The generated PDX in vitro cultures were analyzed for cellular impurities, cancer stem cell content and perpetuation of in vivo PDX characteristics. FACS analyses for tumor specific markers, chemo sensitivity assays and growth characteristics of the PDX derived cell lines (especially for glioblastoma) were analyzed. Results: From PDX tissues used, 90% grew as adherent and/or spheroid PDX derived in vitro cultures, in which mouse cells were entirely depleted. A high percentage of these cultures showed enriched cancer stem cell features and stem cell marker expression. Tumor marker expression and standard drug sensitivity data correlate to the in vivo PDX and derived in vitro cell culture models. RNAseq data were used to predict drug sensitivities in silico for untested drugs and drug combinations on our newly established PDX derived glioblastoma cell lines. Initial screens with predicted candidates were performed. Promising conditions were successfully repeated in corresponding animal PDX models. Conclusion: The newly developed technology for establishment if in vitro cell cultures from PDX efficiently generates stably growing cell lines possessing all key features of the original PDX. These cell lines can be used for initial pre-screens to optimize and improve selection of pharmacologically active drugs or drug combinations before initiating in vivo PDX studies. Citation Format: Lars Winkler, Joshua Alcaniz, Maria Stecklum, Wolfgang Walther, Jens Hoffmann. Adherent and spheroid cell models of patient-derived xenograft for drug development and translational research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4250.

Abstract 6568: PTCH1 loss-of-function alterations: Mutational landscape and therapeutic outcomes to hedgehog pathway inhibitors in non-canonical histologies

Abstract Background: Loss-of-function (LOF) alterations of the PTCH1 tumor suppressor gene represent canonical events involved in basal cell carcinoma (BCC) oncogenesis. Hedgehog pathway inhibitors (HPIs) are approved for the treatment of advanced BCC, but genomic characterization and therapeutic outcomes remain limited in tumor agnostic cohorts. Methods: Using the MSK Clinical Sequencing Cohort, we performed a mutational landscape analysis of PTCH1 LOF alterations in non-BCC histologies, including Fraction and Allele-Specific Copy Number Estimates from Tumor Sequencing (FACETS) annotation, and analyzed response and progression-free survival (PFS) with HPIs. Results: Out of 115,619 samples, 1972 samples from advanced solid tumors with PTCH1 LOF alterations were identified. Excluding 1306 variants of unknown significance (VUSs) using OncoKB knowledge base as well as 44 BCC samples, a total of 622 samples from 570 patients with oncogenic PTCH1 alterations were identified across histologies. In addition, 124 patients received ≥1 line(s) of HPI at our institution between 2013 and 2023, including 16 patients with non-BCC histologies presenting PTCH1 alterations. At the patient level (n=570), PTCH1 LOF alterations were present across 33 primary sites, including colorectal cancer (CRC; 34%; n=192), endometrial cancer (17%; n=98), gastroesophageal adenocarcinomas (ADC) (8%; n=46), non-small cell lung cancer (NSCLC; 6%; n=34) and soft tissue sarcomas (STS; 4%; n=25). At the sample level (n=622), TMB ≥10 was seen in 83% (n=516), including 324 samples with MSI-high status. PTCH1 alterations most frequently involved frameshift (fs) indels (69%; n=429), followed by nonsense mutations (18%; n=114), splice site mutations (8%; n=47) and fusions (5%; n=32). Recurrent fs events involved S1203Afs*52 (24%; n=150) and R1308Efs*64 (14%; n=89), among others. When comparing monoallelic (monoall) vs biallelic (biall) PTCH1 alterations through FACETS annotation, monoall showed a strong association with higher TMB (p<0.01) whereas biall were associated with higher loss of heterozygosity (LOH; p<0.01). In the 16 non-BCC patients treated with HPIs, histologies included lung squamous cell cancer (SCC; n=4), cutaneous SCC (n=2), medulloblastoma (n=2), carcinosarcoma (n=2), osteosarcoma, chondrosarcoma, chordoma, sebaceous ADC, anal SCC and CRC (each n=1). TMB ≥10 was seen in 31% (n=5), all of which were MSI-low. Tumor regressions on HPI were seen in 50% (n=8), including lung SCC, cutaneous SCC, sebaceous ADC and medulloblastoma, with median time to response of 3.6 months (mo). Median PFS on HPI was 3.9 mo and median OS was 22.7 mo. Median PFS was higher in patients with TMB ≥10 vs TMB <10 (11.8 vs. 1.8 mo, p=0.02). Conclusion: PTCH1 LOF alterations appear actionable in non-BCC cutaneous/adnexal primaries, lung SCC and medulloblastoma, including TMB-high tumors. Citation Format: Antoine Desilets, Matteo Repetto, Soo Ryum Yang, Monica Chen, Dazhi Liu, Nikhil Rizvi, Ezra Rosen, Alan L. Ho, Alexander Drilon, Yonina R. Murciano-Goroff. PTCH1 loss-of-function alterations: Mutational landscape and therapeutic outcomes to hedgehog pathway inhibitors in non-canonical histologies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6568.

Abstract 7002: RNA m6A modification and lung cancer risk: An epitranscriptome-wide association study

Abstract N6-Methyladenosine (m6A), the most prevalent epitranscriptomic modification in eukaryotic mRNA, determines the fate of target RNAs. Key m6A regulators have been elucidated to be essential for lung cancer cell proliferation. However, the relationship between individual m6A markers and lung cancer risk remains inadequately explored. We conducted an epitranscriptome-wide association study (EpiTWAS) to investigate genetically predicted m6A in association with lung cancer risk. Genetic and m6A data of 30 lung, 12 heart, 28 muscle, and 50 brain tissues from 87 donors predominantly of European ancestry were obtained from Genotype-Tissue Expression (GTEx). For each m6A marker, we built a single-tissue model via elastic net, focusing on lung tissue, and a cross-tissue model through the unified test for molecular signatures (UTMOST) approach, capturing genetic influences on m6A shared by lung and other tissues. SPrediXcan was used to apply these models to data of genome-wide association studies (GWAS) among 38,422 lung cancer cases and 677,930 controls of European descent from International Lung Cancer Consortium (ILCCO), UK Biobank, and FinnGen. For m6A markers significantly associated with lung cancer risk at false discovery rate (FDR)<0.05, we assessed the differential expression of proteins encoded by their target mRNAs in lung cancer versus adjacent normal tissues (200 pairs), using data from Clinical Proteomic Tumor Analysis Consortium (CPTAC). Of the 38,841 high-quality m6A markers in 11,715 genes analyzed, prediction models were built for 6,809 m6A markers in 4,548 genes with performance of R>0.1 (P<0.05), ~85.2% (5,801) of which were single-tissue models. Among these, 28 m6A markers in 26 genes were significantly associated with overall lung cancer risk (FDR<0.05). Notably, 12 (~43%) of these markers in 12 loci are >2 megabases away from any of GWAS-identified lung cancer risk variants. When conditioning on nearby GWAS signals, these 12 associations did not change materially, whereas 15 of the remaining 16 associations lost statistical significance. Analyses by lung cancer histology and smoking status revealed no significant heterogeneity among the 28 associations but identified eight additional m6A markers significantly (FDR<0.05) associated with the risk of adenocarcinoma (n=2), squamous cell carcinoma (n=3), and overall lung cancer among ever- (n=2) or never-smokers (n=1). Of the 33 target RNAs of those 36 m6A markers, 30 encode proteins and 22 of these proteins displayed a significant tumor-normal differential expression at fold change >1.5 and FDR<0.05 in CPTAC lung tissue data. Our study demonstrates the ability of EpiTWAS to decipher GWAS loci and uncover signals potentially missed by GWAS. Our results imply that certain m6A markers may impact lung cancer risk by modulating mRNA translation, underscoring the need for further research to fully unravel the role of m6A in lung cancer etiology. Citation Format: Yaohua Yang, Yaxin Chen, Yawen Qi, Hongmo Liu, Guochong Jia, Jie Ping, Xiao-Ou Shu, Wei Zheng, Weimin Li, Jirong Long, Qiuyin Cai. RNA m6A modification and lung cancer risk: An epitranscriptome-wide association study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7002.

Abstract 208: FGFR2 splice variant as a cell fate adjudicator determines clinical outcomes in non-small cell lung cancer

Abstract The splice variants specific protein expression in tumor cells presents promising targets for cancer therapy. The concept is supported by the recent introduction of the splice variant-specific antibody against FGFR2 IIIb (FGFR2b) in gastric cancer. Indeed, signaling of the two FGFR2 splice variants FGFR2b and FGFR2 IIIc (FGFR2c), whose expression is mutually exclusive on a cellular level, is mediated by different ligands and distinct downstream responses that can contribute to many aspects of tumorigenesis. Our study aimed to characterize the expression FGFR2b and 2c in non-malignant lung and non-small cell lung cancer (NSCLC) tissue and relate splice variant-specific expression to the histological and molecular background of cancer and its clinical impact.FGFR2b/FGFR2c isoforms expression was determined in RNA-seq data from 180 NSCLC patients and 19 tissues from normal lung (patient-matched). Cell-type specific expression and pan-cancer analysis of FGFR2 were explored using a public database, including DBTSS (NSCLC: 26, normal lung epithelium: 1, normal lung fibroblast 1) and CCLE (Total: 1019, NSCLC: 131), GTEx (normal lung tissue: 578) and HPA (scRNAseq for lung).Our results confirm a cell-specific expression in normal cells with dominance of FGFR2b in epithelial cells and FGFR2c in mesenchymal cells. In normal lung tissue, the FGFR2b variant showed high abundance. Pan-cancer analysis revealed FGFR2c dominant cancers (e.g., CNS tumors, kidney, liver) as well as FGFR2b dominant cancer types (e.g., breast, colon, lung cancer). The RNAseq data from our NSCLC cohort showed a chief expression of FGFR2b in 116 cases (64%), FGFR2c in 31 cases (17%), and a mixed FGFR2c/FGFR2b transcriptomics (18%). The ratio of FGFR2b/FGFR2c as a metric for splice variant dominance was associated with squamous histology, higher stage, and KRAS mutations. Differential gene expression analysis of cancer tissue and cell lines revealed an association of the splice variant FGFR2c to epithelial-mesenchymal transition (EMT) and the regulation of genes (ZEP1, ERSP1, CDH1) involved in the TGF-beta signal pathway. Finally, the ratio of FGFR2b/FGFR2c demonstrated a strong association with overall survival in NSCLC patients with the FGFR2c variant as unfavorable predictors (High vs low ratio, p = 0.01). Our study indicates cell-specific splice variant expression in non-malignant and malignant cells. The prognostic unfavorable impact of the FGFR2c variant on NSCLC patient survival might be explained by its association with TGF signaling and EMT. The observed clinical and biological difference between FGFR2b and FGFR2c dominated cancers gives further rationale to exploit splice variants as therapeutical targets. Citation Format: Hui Yu, Masafumi Horie, Amanda Lindberg, Max Backman, Neda Hekmati, Johanna Mattsson, Naoya Miyashita, Hans Brunnström, Fredrik Ponten, Akira Saito, Carina Strell, Patrick Micke. FGFR2 splice variant as a cell fate adjudicator determines clinical outcomes in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 208.

Abstract 5376: Quantitative profiling of HLA class I and class II antigens and neoantigens in tissue biopsy and PBMC samples using an optimized mass spectrometry-based workflow

Abstract Major histocompatibility complex (MHC) molecules play a central role in orchestrating immune responses by presenting antigenic peptides derived from both self and foreign proteins. In the context of cancer, understanding the repertoire of tumor-associated antigens (TAAs) presented by MHC molecules (or HLA molecules in human) is crucial for deciphering how the immune system recognizes and responds to malignant cells. The identification of neoantigens, unique to individual tumors due to somatic mutations, has become a focal point in immunopeptidomic studies. One significant hurdle in systematic immunopeptidomics analysis is the high input material requirement. Here, we present a semi-automated workflow to robustly identify and quantify immunopeptides from reduced amounts of clinical tissue biopsy and peripheral blood mononuclear cell samples. At the core of immunopeptidomics is the enrichment of HLA-associated peptides, followed by identification using mass spectrometry and bioinformatics tools. We optimized the native lysis and a sequential immunoprecipitation workflow for both class I and class II immunopeptides while ensuring scalability and reproducibility. Leveraging the magnetic properties of the beads, 1,000 samples can be processed within a week by a single operator. For both tissue and PBMC samples, we performed a systematic ramping experiment starting with as little as 2.5mg tissue or 5 million PBMCs. In all experiments, The established sample preparation offers high reproducibility and identifications of good quality: 1) Class-I immunopeptides: >60% of the peptides identified are 9-mers, >80% predicted strong binders, and the expected amino acids are enriched at the anchor positions; 2) Class-II immunopeptides, >50% of the peptides identified are 14-to-16-mers, and >50% are predicted strong binders. Furthermore, the pipeline is highly sensitive as we could still identify over 2,800 class-I immunopeptides when processing 2.5 mg fresh frozen tissue and 2,000 - 3,000 class-I immunopeptides when starting from 5 million PBMCs. Furthermore, the developed immunopeptidomics workflow was deployed to profile a cohort of 12 cancerous and matched healthy lung tissue samples. Their Class-I immunopeptidomes clearly displayed a pattern where matched tissues from each subject cluster together, further underlining the fact that the intricate immune-tumor interface is highly personalized. Overall, we established a robust pipeline for for class-I and II immunopeptidome profiling from clinically relevant sample types. Taking advantage of the nature of mass spectrometry-based methods, customized targeted assays can be developed without the need for affinity reagent, allowing specific and absolute quantification of any immunopeptide of interest. Citation Format: Ilja E. Shapiro, Marco Tognetti, Tikira Temu, Oliver M. Bernhardt, Daniel Redfern, Yuehan Feng, Roland Bruderer, Lukas Reiter. Quantitative profiling of HLA class I and class II antigens and neoantigens in tissue biopsy and PBMC samples using an optimized mass spectrometry-based workflow [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5376.

Abstract 1141: Spatial-specific gene signatures to predict immunotherapy outcomes in lung cancer

Abstract The widespread use of immunotherapy in lung cancer, and its more recent approval for early stages, underscores the need for biomarkers that can identify the most responsive patients. Spatial transcriptomics, which maps gene expression in its spatial tissue context, offers a unique approach over bulk transcriptomics. By incorporating spatial information, the predictive power of the signature can be enhanced. Here, we aim to develop spatially informed gene signatures that could be translated into clinical RNA in situ assays, distinguishing patients unlikely to benefit from immunotherapy and thereby sparing them unnecessary side effects. We utilized the NanoString GeoMX Whole Transcriptome Atlas for spatially resolved transcriptomic profiling of retrospectively collected lung cancer tissue samples from patients treated with immunotherapy in an advanced-stage setting (N=60). By targeting 18,190 genes within distinct areas of interest (AOIs)—including stromal (macrophages/CD68+ and leukocytes/CD45+) and tumor (cytokeratin, CK+) cells—we developed AOI-specific gene signatures to predict objective responses. These were derived from a robust computational framework employing LASSO logistic regression on a split-sample approach, yielding predictive models for treatment outcome.We achieved high predictive accuracy on the training set, with the area under the curve (AUC) exceeding 0.86 for all AOI-specific spatial signatures, indicating strong potential for clinical application. Validation against an independent cohort (N=42) corroborated the efficacy of these signatures. Our 6-gene tumor signature was validated with an AUC of 0.73 (95% CI: 0.67-0.89, p = 0.009**), while the CD45 5-gene signature showed an AUC of 0.75 (95% CI: 0.53-0.97, p = 0.022*). Our 18-gene CD68 signature trended towards validation but lacked statistical significance. A combined CD68 and CD45 signature predicted outcomes with greater accuracy, achieving an AUC of 0.79 (95% CI: 0.62-0.98, p = 0.0088*). Following gene set enrichment analysis on our differentially expressed and signature genes, we identified genes with positive coefficients in both tumor and stroma signatures that were associated with glucocorticoid response and glycolytic processes linked to T-cell homeostasis, while genes with negative coefficients were associated with epithelial cell differentiation and cytokine production. These associations are concordant with the observation that genes with positive coefficients are predictors of treatment response, while those with negative coefficients indicate resistance.Our findings indicate that AOI-specific signatures predict the immunotherapy outcome in lung cancer with high accuracy, suggesting that spatial assessment can provide substantial predictive information. The high performance of these signatures indicates their potential for prospective clinical applications. Citation Format: Thazin N. Aung, Myrto Moutafi, Ioannis Trontzas, Arutha Kulasinghe, James Monkman, Niki Gavrielatou, Ioannis Vathiotis, Jonathan H. Warrell, David L. Rimm. Spatial-specific gene signatures to predict immunotherapy outcomes in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1141.

Abstract 7362: Integrated analysis of scRNAseq and spatial omics in brain metastatic lung cancer tumor tissue

Abstract Spatial omics technologies have made significant advances in recent years, improving our understanding of the spatial localization of cells and intercellular interactions. Intercellular interactions are essential for maintaining proper tissue function and homeostasis, and dysregulation of these interactions can contribute to various diseases, including cancer and autoimmune disorders. Ligand proteins, one of the signaling molecules responsible for cell-cell interactions, bind to cell surface receptors and trigger intracellular signaling pathways. The effective range of ligand signaling, i.e. the extent to which a cell spatially and directly transmits information via the ligand, has not been systematically studied, although it may determine the occurrence of cell-cell interactions. The authors have previously developed methodologies combining spatial transcriptomics and single-cell RNA sequencing to analyze intercellular interactions at the single-cell level in spatial dimensions. Additionally, we have devised a technique to model the spatial diffusion of ligands from spatial transcriptomics and estimate the spatial range of ligand action. In this study, we used these developed methods to elucidate events in the tumor microenvironment of brain metastatic lung cancer tissue. Specifically, an integrated analysis of metastatic brain tumor samples was performed using visium and single-cell data from the same patient. The results suggest the presence of a heterogeneous microglial subpopulation, including clusters enriched in cytokines and chemokines for angiogenesis and wound healing, clusters associated with immune tolerance via IL-10 signaling, clusters enriched in gene sets related to phagocytosis, antigen processing, and antigen presentation, and clusters related to clearance of pathogens and residues. The presence of homogeneous microglial subpopulations was suggested. Furthermore, these subpopulations exhibited different spatial distributions, suggesting that they interact with surrounding cancer cells through different mechanisms. Citation Format: Haruka Hirose, Takahiro Tsuji, Yasuhiro Kojima, Akihiko Yoshizawa, Yoshiki Arakawa, Hiroaki Ozasa, Hiroaki Wake, Teppei Shimamura. Integrated analysis of scRNAseq and spatial omics in brain metastatic lung cancer tumor tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7362.